The rapid development of Internet makes it more serious the overloading phenomenon of information in electronic commerce. How to find goods required quickly and accurately from the commodity information is a problem that needs to solve. Recommendation personalized offers a solution to the problem. In order to achieve an accurate recommendation, this paper presents the use of artificial immune clustering technology to the user, and then to recommend using collaborative filtering. It shows that the accuracy rate can reach 80% in the experiment.